fact-check — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited fact-check (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
This skill verifies a specific claim by searching for evidence on both sides, evaluating source quality, and delivering a clear verdict.
Search — run the packaged Web Forager CLI with uvx:
uvx --python '>=3.10,<3.14' web-forager search "your query" --max-results 8 --output-format jsonIf uvx cannot run the packaged CLI, use a direct ddgs fallback through uv without touching the current project environment:
uv run --no-project --python '>=3.10,<3.14' --with 'ddgs>=9.5.2' python - <<'PY'
from ddgs import DDGS
results = DDGS().text(query="your query", max_results=8)
for r in results:
print(r["title"], r["href"], r["body"])
PYFetch — call Jina Reader directly to get a URL as clean markdown:
curl -s "https://r.jina.ai/https://example.com"Or in Python:
import requests
content = requests.get(f"https://r.jina.ai/{url}").textIf MCP search/fetch tools are available in the session (e.g., mcp__web_forager__search, mcp__duckduckgo__search, or similar), prefer those over the above.
Identify the specific, verifiable claim. If the user's statement is vague or compound, break it into distinct claims and address each one. Restate the claim back to the user so they can confirm you understood it correctly.
Bad: "AI is taking over" (too vague to verify) Good: "OpenAI's revenue exceeded $3 billion in 2024" (specific, verifiable)
If the claim is inherently subjective or a matter of opinion ("React is better than Vue"), say so upfront — opinion claims can't be fact-checked, only contextualized.
Search for sources that would confirm the claim. Frame queries to find the claim stated as fact:
Now actively look for the other side. This is the step most people skip, and it's the most important one. Frame queries to find disagreement:
From both searches, pick the 2–4 most authoritative sources to fetch in full. Prioritize:
Weigh the evidence. Consider:
## Claim
> [The claim being checked, stated clearly]
## Verdict: [CONFIRMED / LIKELY TRUE / UNVERIFIED / DISPUTED / FALSE]
[2–3 sentence explanation of the verdict — why this rating, what the key evidence is]
## Evidence supporting the claim
- [Specific finding with source citation] — [Source Name](url)
- ...
## Evidence against the claim
- [Specific finding with source citation] — [Source Name](url)
- ...
(If no contradicting evidence was found, say so explicitly)
## Caveats
[Anything that limits confidence: old data, limited sources, nuance the binary
verdict doesn't capture]
## Sources
1. [Title](url) — [brief note on what this source is]Be honest about uncertainty. "Unverified" is a perfectly valid result — it's better than guessing. If the evidence is mixed, say so and explain why.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.